Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns.
FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters.

FABIA is an R package while the code is written in C.

Applications:

microarray: genes that are diffentially expressed in certain samples form a bicluster with these samples, e.g. genes of a pathway that is activated in certain samples.

genetics: researchers want to identify haplotypes shared by different individuals due to >identity by descent<. Especially rare variants in next generation sequencing that form an identity by descent block are identified by fabia (spfabia).

Changes to previous version:

CHANGES IN VERSION 2.4.0

o spfabia bugfixes

CHANGES IN VERSION 2.3.1

NEW FEATURES

o Getters and setters for class Factorization

2.0.0:

spfabia: fabia for a sparse data matrix (in sparse matrix
format) and sparse vector/matrix computations in the code
to speed up computations.
spfabia applications:
(a) detecting >identity by descent< in next generation
sequencing data with rare variants,
(b) detecting >shared haplotypes< in disease studies based
on next generation sequencing data with rare variants;